Generative AI Instructor

The Generative AI Instructor at PNY Trainings delivers in-depth, project-based educational experiences focusing on Artificial Intelligence and Data Science topics. This role emphasizes teaching foundational and advanced concepts such as Python programming, Data Science techniques, Machine Learning algorithms, Deep Learning architectures, Natural Language Processing, and Big Data processing using industry-standard tools and frameworks. The instructor ensures that students gain hands-on experience with practical AI applications by guiding them through the development, evaluation, and deployment of AI models. Maintaining alignment with current AI industry trends, ethical standards, and emerging technologies is a critical aspect of this position to provide students with relevant and up-to-date knowledge. This instructor role requires a seasoned professional with several years of industry and teaching experience in AI-related fields. While the position does not involve managing a team, it demands strong mentorship capabilities to support students’ project work, monitor academic progress, and advise them on career development opportunities such as internships and certifications. The role demands excellent communication and analytical skills, combined with a commitment to continuous learning and adapting to rapid advancements in generative AI and data science.

Compensation: PKR 1500 -2000 Per lecture (2-hour Physical)

(Negotiable & may exceed the stated range)

Responsibilities

Deliver comprehensive theoretical and practical training following the approved course outlines, completing all topics within the stipulated timeline.
Teach core AI fundamentals including Python and R programming, data handling, visualization, and statistical analysis relevant to data science.
Instruct machine learning concepts, model creation, evaluation, and optimization utilizing standard libraries and tools.
Guide students in deep learning topics encompassing neural networks, convolutional neural networks, TensorFlow, and Keras through applied projects.
Conduct practical sessions on Natural Language Processing techniques such as text preprocessing, sentiment analysis, and word embeddings.
Demonstrate big data processing with Apache Spark including Spark SQL, data frames, and distributed data analysis.
Mentor learners through real-world projects to develop end-to-end AI solutions, from data collection and preparation to training and deploying machine learning models.
Develop and administer labs, assignments, quizzes, and comprehensive project evaluations, providing timely and constructive feedback to learners.
Support students in building strong AI-focused portfolios and prepare them for professional advancement via internships, freelancing opportunities, and certifications.
Continuously update the curriculum to align with evolving AI technologies, ethical AI standards, and industry best practices, ensuring students receive relevant instruction.
Foster an engaging and inclusive learning environment that accommodates learners of varying skill levels and backgrounds.
Maintain a strong professional commitment to ethical AI practices, encouraging responsible AI development and application among students.